Lodestar.Embeddings 0.7.0. This page is frozen at that release. Read the current documentation for what main says now. A link to a decision or a migration page follows main, and leaves the archive.

A window of encoded rows, laid out as one rectangle.

public EncodedBatch Pad(IReadOnlyList<long[]> sequences, int start, int count, int[] order = null)

Parameters — sequences are unpadded encodings, as EncodeAll returns them. start and count select the window to lay out. order is an optional indirection: with it, row i of the batch is sequences[order[start + i]], which is how length grouping is expressed without reordering sequences itself.

Returns — EncodedBatch, padded to the longest row in this window — not to MaxLength, and not to the longest row in sequences.

Exceptions — ArgumentNullException when sequences is null. ArgumentOutOfRangeException when start or count is negative, or when the window reaches past the end of sequences (or of order, when one is given).

Example — the same two texts, first together, then the long one alone.

using Lodestar.Embeddings.Tokenization;

var vocab = new Dictionary<string, int>(StringComparer.Ordinal)
{
    ["[UNK]"] = 0, ["token"] = 1, ["##ize"] = 2, ["text"] = 3,
    ["[CLS]"] = 4, ["[SEP]"] = 5, ["[PAD]"] = 6,
};
var tokenizer = new WordPieceTokenizer(
    vocab, unkToken: "[UNK]", continuationPrefix: "##", maxCharsPerWord: 100, lowercase: true);

var encoder = new BatchEncoder(tokenizer, new EncodingOptions
{
    Template = SpecialTokenTemplate.Bert,
    MaxLength = 8,
});

IReadOnlyList<long[]> sequences = encoder.EncodeAll(["text", "tokenize text"]);

EncodedBatch both = encoder.Pad(sequences, 0, 2);
int width = both.SequenceLength;         // => 5

EncodedBatch shortOnly = encoder.Pad(sequences, 0, 1);
int narrower = shortOnly.SequenceLength; // => 3

Remarks — the second call is the whole reason this is public. Padding per window rather than per corpus is what makes grouping worth doing: three rows of length 3 cost a 3-wide rectangle, and only the window that actually contains a 512-token row pays for one.

A window of zero rows still gets one column, masked off. An empty dimension is a tensor shape an inference runtime will refuse, and "no tokens" has to be expressible.

Applies to — net10.0, netstandard2.0.

See also — BatchEncoder.EncodeAll, BatchEncoder.EncodeBatch, EncodedBatch.